LAUSR

Finding the shortest path to the destination is a vital need for autonomous mobile robots. In this article, a smart adaptive particle swarm optimization (APSO) algorithm is proposed for robot path planning. It allows the robot to reach the target point with the shortest possible path and to avoid the obstacles safely in uncertain environments. A new objective function is derived with distance function and a path smoothening parameter is integrated to avoid sharp turns. The results of the proposed method rely on computer simulation and real robot experimentation in different environments. It is proved that they are in good agreement. A comparative study between the proposed algorithm and various other algorithms is also presented. The results showed that the proposed smart algorithm is capable of successfully avoiding various types of obstacles including the local minima situation.